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生成型人工智能是否对性能有效性测试安全性构成风险?

Shannon Lavigne1, Anthony Rios2, Jeremy J Davis1

  • 1Department of Neurology, The University of Texas Health Science Center at San Antonio, TXUSA.

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此摘要是机器生成的。

人工智能 (AI) 聊天机器人对性能验证测试 (PVT) 构成安全风险. 虽然人工智能响应的准确性有所提高,但对PVT安全的重大威胁仍然存在,超过了传统搜索引擎.

关键词:
人工智能聊天机器人人工智能的人工智能是人工智能.生成型的人工智能性能有效性,测试安全性,测试安全性

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科学领域:

  • 神经心理学 神经心理学
  • 人工智能的人工智能
  • 网络安全 网络安全

背景情况:

  • 性能有效性测试 (PVT) 对于确保神经心理评估的有效性至关重要.
  • 人工智能聊天机器人的兴起为测试安全性和数据完整性带来了新的挑战.

研究的目的:

  • 评估人工智能聊天机器人对性能有效性测试 (PVT) 构成的安全风险.
  • 评估人工智能对神经心理评估和PVTs的反应的准确性和威胁水平.

主要方法:

  • 在2023-2024年,生成人工智能网站 (ChatGPT-3,Bard/Gemini) 被查询.
  • 使用了两组查询:一般精细化和直接请求"如何作弊".
  • 人工智能响应被评为不准确性和威胁级别 (没有,轻度,中度,高).

主要成果:

  • 不准确率从35-42% (2023) 降低到16-28% (2024). 不准确率从35-42% (2023) 降低到16-28% (2024). 不准确率从35-42% (2023) 降低到16-28% (2024).
  • 中等/高威胁评级从24-41% (2023) 下降到17-31% (2024).
  • 聊天GPT-3显示精度有所提高;巴德/双子并没有显著变化. 随着时间的推移,对假装查询的道德反对逐渐增加.

结论:

  • 人工智能聊天机器人对PVT安全构成重大威胁.
  • 尽管提高了准确性和增加了道德反对,但人工智能的自然语言界面和响应量比传统搜索引擎构成更大的风险.